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list_opportunity_notes

List notes for a Lever opportunity. Default output shows note metadata and whether body text exists; full note values require detail_profile=full with a reason.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoResults per page. Lever accepts 1-100; default is endpoint-specific.
cursorNoLever pagination offset token from a previous response. Use next_cursor from the prior tool result.
reasonNoRequired when detail_profile requests contact, content, values, or full details.
detail_profileNooperational returns an operations view; full returns the raw endpoint payload.operational
opportunity_idYesLever opportunity ID.

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and adds useful behavioral context: default is metadata-only, full values require a reason. This explains a non-obvious behavior. However, it omits other behaviors like pagination mechanics or response format, so it is not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the primary action. Every clause adds information: listing notes, default behavior, and the requirement for full details. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core function and the key detail-profile caveat but lacks guidance on pagination (though limit/cursor are in schema) and does not describe the return structure beyond 'metadata and body text existence'. Given the absence of an output schema, the description should provide more context for a list operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by connecting detail_profile=full with the reason requirement, clarifying the interaction between these parameters beyond their individual schema descriptions. This is a meaningful addition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'List notes for a Lever opportunity' with a specific verb ('List') and resource ('notes for a Lever opportunity'). This distinguishes it from sibling tools like get_opportunity_note (singular) and other list_* tools by targeting opportunity notes specifically.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It implies when to use the default output vs. full detail via 'detail_profile=full with a reason', but it does not explicitly mention alternatives or when not to use this tool. For example, it does not point to get_opportunity_note for retrieving a single note. Usage context is present but not fully articulated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation4/5

Most tools target distinct resource-action combinations, but the sheer count (108) and the presence of closely related tools like list_opportunity_feedback / get_opportunity_feedback may cause occasional agent confusion.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun pattern (e.g., create_*, get_*, list_*, update_*, delete_*, add_*, remove_*). Minor exceptions like apply_to_posting still fit the overall structure.

Tool Count2/5

With 108 tools, the surface is excessively large for most agent workflows. Many tools could be merged or removed without losing essential functionality, leading to decision overload.

Completeness5/5

The tool set covers the full Lever API surface comprehensively, including opportunities, postings, requisitions, users, webhooks, templates, files, and compliance data, leaving no obvious gaps.

Resources